Note: Descriptions are shown in the official language in which they were submitted.
ESTIMATE ACTIVE-ADJACENT BOREHOLE INTERFERENCE SEVERITY
TECHNICAL FIELD
[0001] This application is directed, in general, to determining a hydraulic
fracturing treatment
stage plan and, more specifically, to determining a magnitude of a leak-off
event.
BACKGROUND
[0002] When developing a well system, fluid is often pumped into the well
system as part of a
treatment plan. For example, the fluid can be a fracturing fluid in a
hydraulic fracturing well
system. When this is done near a void, such as an adjacent borehole or a
depleted reservoir,
some of the hydraulic fluid can leak off into that other void. This can be
detected because the
volume of fluid that is pumped into the borehole is larger than what the
borehole can hold. As
fluid leaks off into the void, the efficiency of the fluid in the active well
system decreases, for
example, the fluid pressure can drop. Understanding the amount or magnitude of
leak-off that is
occurring would be beneficial.
SUMMARY
[0003] In one aspect, a method is disclosed. In one embodiment, the method
includes (1)
receiving input parameters from one or more adjacent boreholes in a reservoir,
(2) performing a
treatment stage of an active borehole proximate the one or more adjacent
boreholes, (3)
monitoring the input parameters of the one or more adjacent boreholes, wherein
the input
parameters are received at a periodic time interval, and (4) determining a
leak-off event with one
or more of the one or more adjacent boreholes by utilizing one or more of
monitoring a change in
an adjacent fluid pressure or an adjacent fluid volume of the one or more of
the one or more
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Date Recue/Date Received 2020-12-23
adjacent boreholes, wherein the adjacent fluid pressure exceeds a fracture hit
threshold or the
adjacent fluid volume exceeds a leak-off threshold.
[0004] In a second aspect, a system that includes an active borehole of a
reservoir undergoing at
least one treatment stage where pumped fluid is pumped into the active
borehole is disclosed. In
one embodiment, the system includes (1) a well site controller, capable of
directing operation of
the active borehole and directing an adjustment of the pumped fluid, and where
the reservoir
includes at least one adjacent borehole, and (2) a leak-off event estimator,
capable of receiving
input parameters from the at least one adjacent borehole and the well site
controller at a periodic
time interval, and determining a leak-off event, wherein the leak-off event is
determined using a
fracture hit threshold or a leak-off threshold.
[0005] In a third aspect, a computer program product having a series of
operating instructions
stored on a non-transitory computer-readable medium that directs a data
processing apparatus
when executed thereby to perform operations to determine a leak-off event is
disclosed. In one
embodiment, the computer program product has operations including (1)
receiving input
parameters from one or more adjacent boreholes in a reservoir, (2) directing a
treatment stage of
an active borehole proximate the one or more adjacent boreholes, (3)
monitoring the input
parameters of the one or more adjacent boreholes, wherein the input parameters
are received at a
periodic time interval, and (4) determining a leak-off event with one or more
of the one or more
adjacent boreholes by utilizing one or more of monitoring a change in an
adjacent fluid pressure
or an adjacent fluid volume of the one or more of the one or more adjacent
boreholes, wherein
the adjacent fluid pressure exceeds a fracture hit threshold or the adjacent
fluid volume exceeds a
leak-off threshold.
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Date Recue/Date Received 2020-12-23
BRIEF DESCRIPTION
[0006] Reference is now made to the following descriptions taken in
conjunction with the
accompanying drawings, in which:
[0007] FIG. 1 is an illustration of a diagram of an example hydraulic
fracturing (HF) well
system;
[0008] FIG. 2 is an illustration of a diagram of an example fluid volume graph
for an adjacent
borehole;
[0009] FIG. 3 is an illustration of a diagram of an example graph to monitor
adjacent borehole
pressure changes;
[0010] FIG. 4 is an illustration of a diagram of an example graph to predict a
leak-off event;
[0011] FIG. 5 is an illustration of a flow diagram of an example method to
monitor an adjacent
borehole for a leak-off event; and
[0012] FIG. 6 is an illustration of a block diagram of an example leak-off
estimator system.
DETAILED DESCRIPTION
[0013] When developing a borehole system, such as a hydraulic fracturing (HF)
well system, a
scientific borehole system, or other types of borehole systems, a treatment
plan can include a
stage for pumping a fluid into the active borehole. The fluid can be one or
more, or a
combination of, various types of fluids, for example, oil, water, brine,
chemicals, diverters,
hydraulic fluids, slurry, proppant, and other fluids with various additives.
The fluid pumped into
a borehole location, e.g., downhole material, can perform a function to
develop the borehole, for
example, fracturing a portion of the surrounding subterranean formation or
blocking a fluid path
with diverter material.
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Date Recue/Date Received 2020-12-23
[0014] During the treatment stage, the ability to place a maximum possible
amount of fluid, for
example, proppant or slurry, in the borehole system, e.g., reservoir, can be
important for the
efficiency of the treatment stage. Presence of a depleted reservoir adjacent
to the active
borehole, e.g., adjacent borehole, void, reservoir, or other subterranean
formation area
(collectively, adjacent borehole system), can result in well-interference, and
hence loss of the
fluid to the depleted reservoir, e.g., a leak-off event.
[0015] The effectiveness of the pumped fluid performing its function can be
reduced if a portion
of the pumped fluid leaks off into another void. Understanding the amount or
magnitude of the
leak-off can improve decision making by a controller, such as a well site
controller or a user.
Decisions can be made to adjust the pressure, volume, or rate of the pumped
fluid, or diverter
material can be increased or decreased in the pumped fluid. Being able to
determine these
decisions can improve the efficiency of developing the borehole and thereby
reduce operating
costs.
[0016] This disclosure presents processes that can be implemented to determine
the amount or
magnitude of a potential leak-off event in real-time or near real-time. The
disclosed processes
can be implemented by one or more computing systems capable of receiving input
parameters,
performing the described calculations, and outputting the result parameters to
a controller, a
computing system, or a user. The computing system can be a well site
controller, a smaiiphone,
mobile phone, PDA, laptop, server, data center, cloud environment, and can be
located
proximate the active borehole or a distance from the active borehole. In some
aspects, the input
parameters can be the fluid volume and the fluid pressure measurements over a
time interval for
the adjacent boreholes. In some aspects, the input parameters can include
adjacent borehole
system characteristics, reservoir characteristics, and subterranean formation
characteristics. In
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Date Recue/Date Received 2020-12-23
some aspects, the active borehole pressure can be measured at a surface
location. In some
aspects, the processes can be applied to pressure measurements measured at one
or more
locations within the active borehole.
[0017] As a decision is made utilizing the leak-off event data, adjustments to
the pumped fluid
parameters can be made, for example, an adjustment to the pump volume, the
pump rate, or the
pump pressure. In addition, the fluid composition can be adjusted, for
example, adding diverter
material, adjusting the amount of diverter material, or adjusting the
composition of the pumped
fluid, such as adjusting the amount of oil, water, brine, chemicals,
additives, proppant, slurry, or
other hydraulic fluids.
[0018] As the pumped fluid parameters or composition are adjusted, the
disclosed processes can
recalculate the estimated leak-off event data in real-time or near real-time
so a controller or a
user can monitor the effectiveness of the adjustments made and determine
whether further
adjustments should be made to the pumped fluid parameters or composition. The
described
processes can improve the efficiency of developing the borehole, e.g., well
system, thereby
lowering operating costs.
[0019] In some aspects, a real-time or near real-time recording of pressure
fluctuations on one or
more parent wells, e.g., adjacent boreholes, during the treatment stage of an
active well,
translated into fluid volume invading the depleted reservoir boundary, e.g.,
misplaced slurry, can
be utilized to quantify the severity of interference on the active borehole by
the one or more
adjacent borehole systems, to enable deployment of control techniques to
mitigate the severity.
[0020] Turning now to the figures, FIG. 1 is an illustration of a diagram of
an example HF well
system 100, which can be a well site where HF operations are occurring through
the
implementation of a HF treatment plan. HF well system 100 demonstrates a
nearly horizontal
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Date Recue/Date Received 2020-12-23
borehole undergoing a fracturing operation. Although FIG. 1 depicts a specific
borehole
configuration, those skilled in the art will understand that the disclosure is
equally well suited for
use in boreholes having other orientations including vertical boreholes,
horizontal boreholes,
slanted boreholes, multilateral boreholes, and other borehole types. FIG. 1
depicts an onshore
operation. Those skilled in the art will understand that the disclosure is
equally well suited for
use in offshore operations. FIG. 1 depicts a HF well system and the disclosed
processes can be
utilized for other borehole types, for example, scientific boreholes, drilling
boreholes, and other
type of boreholes and well systems.
[0021] HF well system 100 includes a surface well equipment 105 located at a
surface 106, a
well site controller 110, and a HF pump system 114. In some aspects, well site
controller 110 is
communicatively connected to a computing system 112, for example, a server, a
data center, a
cloud service, a tablet, a laptop, a smartphone, or other types of computing
systems. Computing
system 112 can be located proximate to well site controller 110 or located a
distance from well
site controller 110. Computing system 112 can be utilized by a well system
engineer or operator
to review leak-off event data or to direct recommendations to a pumping plan
generator or well
site controller 110.
[0022] Extending below surface 106 from surface well equipment 105 is a
borehole 120.
Borehole 120 can have zero or more cased sections and a bottom section that is
uncased.
Inserted into the borehole 120 is a fluid pipe 122. The bottom portion of
fluid pipe 122 has the
capability of releasing pumped fluid 125 from fluid pipe 122 to the
surrounding subterranean
formation 140. The release of pumped fluid 125 can be by perforations in fluid
pipe 122, by
valves placed along fluid pipe 122, or by other release means. At the end of
fluid pipe 122 is a
bottom hole assembly (BHA) 130. BHA 130 can be one or more downhole tools,
including an
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Date Recue/Date Received 2020-12-23
endcap assembly. Proximate borehole 120 is an adjacent borehole 160 that has
an endcap 165.
For demonstration purposes, fluid 170 is shown as having leaked into borehole
160 from
borehole 120 through one of the fracture clusters 142.
[0023] In HF well system 100, fluid pipe 122 is releasing pumped fluid 125
into subterranean
formation 140 at a determined HF fluid pressure and HF fluid flow rate. Pumped
fluid 125 is
being absorbed by, e.g., enter or flowing into, several fracture clusters 142.
The leak-off event
data computed can be utilized as an input into a pumping plan for HF well
system 100, such as
for the pumping plan of the treatment stage. The insights gained from the leak-
off computation
result parameters can be used by well site controller 110 or computing system
112 to modify the
treatment stage, such as adjusting the concentration or composition of pumped
fluid 125,
adjusting the timing of release of diverter material or other downhole
material, or adjusting the
HF fluid pressure, HF fluid flow rate, or HF fluid volume of pumped fluid 125.
[0024] Well site controller 110 can include a well site parameter collector
that can collect sensor
data from sensors proximate to the well site and located within the borehole,
such as a downhole
HF fluid pressure gauge and a DAS. In some aspects, well site controller 110
and computing
system 112 can include a leak-off estimator system capable of receiving
downhole data, such as
HF fluid pressure, HF fluid flow rate, physical model parameters, borehole
parameters, input
parameters from adjacent boreholes, and other data, and compute the leak-off
event data.
[0025] In an alternative aspect, computing system 112 can be located a
distance from HF well
system 100, such as in a data center, server, or other system, and computing
system 112 can be
disconnected from HF well system 100. In this aspect, computing system 112 can
receive
physical model parameters, along with the borehole parameters, treatment stage
parameters, and
other input parameters, where the various parameters were collected by the
other components of
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Date Recue/Date Received 2020-12-23
HF well system 100. In some aspects, the leak-off event estimator can be part
of computing
system 112 and can produce a recommendation on the modifications to the
treatment stage.
[0026] FIG. 2 is an illustration of a diagram of an example fluid volume graph
200 for an
adjacent borehole. Fluid volume graph 200, generated from data collected from
an adjacent
borehole, can be utilized as a pressure-volume model. Fluid volume graph 200
has an x-axis 205
showing an increasing pressure. A y-axis 206 shows an increasing volume of
fluid. A plot area
210 shows line plot 220 of an adjacent borehole showing the pressure-volume
curve.
[0027] FIG. 3 is an illustration of a diagram of an example graph 300 to
monitor adjacent
borehole pressure changes as fluid is pumped into the active borehole. As the
pumped fluid is
pumped into the active borehole over time, changes can be measured for the
pressure of the fluid
in the active borehole and the adjacent borehole. Graph 300 has an x-axis 305
showing time, and
a y-axis 306 showing increasing pressure. A plot area 310 has three line plots
and event points.
[0028] A line plot 320 shows an example pumped fluid flow rate over time. A
line plot 322
shows an example pumped fluid pressure changing over time. A line plot 324
shows an example
pressure rate measured in an adjacent borehole. Point P1 330 indicates a point
where the
pressure in the adjacent borehole begins to increase at a higher rate than at
a previous point in
time. The increased rate of pressure can be indicative of a leak-off event.
Point P2 335 indicates
an arbitrary point after point P1 330. The input parameters gathered at point
P1 330 and point P2
335 can be utilized by the methods described in FIG. 5.
[0029] FIG. 4 is an illustration of a diagram of an example graph 400 to
predict a leak-off event
using machine learning algorithms. Graph 400 can be generated using input
parameters received
from an adjacent borehole in real-time or near real-time, or from a data
storage, for example, a
hard disk, database, memory, cloud environment, or other storage areas. Graph
400 has an x-
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Date Recue/Date Received 2020-12-23
axis 405 showing increasing time and a y-axis 406 showing increasing pressure.
A plot area 410
shows line plots similar to graph 300 of FIG. 3, with a focus on the bottom
portion of graph 300.
[0030] A line plot 420 is a portion of a pumped fluid rate line, similar to
line plot 320. A line
plot 424 is a portion of line plot 324 from graph 300, with a focus around a
point 430, similar to
point P1 330. The left side of point 430, shown by the vertical dashed line,
represents a learn 440
portion of the analysis. The right side of point 430 represents a predict 445
portion of the
analysis.
[0031] The machine learning algorithm can utilize the received information to
perform analysis
in support of the processes described herein. A fitted line 432 can be fitted
to line plot 424 in
learn 440 portion. A fracture hit threshold can be utilized to determine a
range of values that can
satisfy fitted line 432, this calculated range is shown by threshold lines 434
in learn 440 portion.
In predict 445 portion, fitted line 432 and threshold lines 434 are estimated
as shown by
prediction 450. Point 430 is the point where line plot 424 no longer satisfies
the fracture hit
threshold, therefore a leak-off event is likely occurring and should be
analyzed more closely by a
computing system or a user.
[0032] FIGs. 2, 3, and 4 demonstrate graphs that can be utilized to assist in
the disclosed analysis
and processes. These graphs are for demonstration purposes and are not
necessary for the
implementation of the disclosed processes. The disclosed processes can be
implemented within
a computing system where the input parameters are stored and manipulated in a
form appropriate
for the computing system without a graphing or visual component.
[0033] FIG. 5 is an illustration of a flow diagram of an example method 500 to
monitor an
adjacent borehole system for a leak-off event. Method 500 can be performed on
a computing
system, such as a well site controller, a leak-off event estimator, or other
computing system
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Date Recue/Date Received 2020-12-23
capable of receiving the input parameters, and capable of communicating with
equipment or a
user at a well site, for example, well site controller 630 of FIG. 6. Other
computing systems can
be a smaitphone, a mobile phone, a PDA, a laptop computer, a desktop computer,
a server, a data
center, a cloud environment, or other computing system. Method 500 can be
encapsulated in
software code or in hardware, for example, an application, a code library, a
dynamic link library,
a module, a function, a RAM, a ROM, and other software and hardware
implementations. The
software can be stored in a file, database, or other computing system storage
mechanism.
Method 500 can be partially implemented in software and partially in hardware.
[0034] Method 500 starts at a step 505 and proceeds to a step 510 or a step
520. Step 510 can be
selected when input parameters from the adjacent borehole system are
available. Step 520 can
be selected when input parameters from the adjacent borehole system are not
available and a
machine learning process can be utilized. When step 510 is selected, the
processes can receive
adjacent borehole system input parameters. There can be one or more adjacent
borehole systems
utilized in the processes. In some aspects, the adjacent borehole system input
parameters can be
the water-injection data or re-fracture data for the adjacent borehole
systems. In some aspects,
the adjacent borehole system input parameters can correspond to pressure and
flow-rate
recording over the time interval of interest. Using the flow-rate time-series
data, the volume
injected can be computed and, in some aspects, a fluid pressure vs. fluid
volume chart can be
generated. In some aspects, the fluid pressure can be translated to bottom-
hole conditions by
applying the appropriate vertical depth parameter. An example of the fluid
pressure vs. fluid
volume curve is shown in FIG. 2. In some aspects, the data utilized to
generate the fluid pressure
vs. fluid volume curve can be utilized as a look-up table to obtain a volume
of the fluid for a
given fluid pressure in the borehole.
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Date Recue/Date Received 2020-12-23
[0035] In some aspects, the fluid pressure vs. fluid volume data can be
utilized to infer borehole
and reservoir specific characteristics, for example, a system compressibility
parameter (Cr), a
leak-off coefficient (Lk), and a time shift factor (to) by fitting Equation 1
to the data. The fluid
volume in the borehole for a given fluid pressure at a given time can be
computed utilizing these
estimated coefficients.
Equation 1: Example calculating fluid volume using estimated borehole
characteristic
coefficients
AV = Cp (Pp ¨ Pp, s) ¨ 2 Lk(Vt + to ¨ Vts + to)
where AV is the calculated fluid volume,
Cp is the system compressibility parameter utilizing the initial fluid
pressure Pp,s and a
measured point in time (t) pressure Pp, and
Lk is the leak-off coefficient over a time interval identified by a start time
ts, a time shift
factor to, and the point in time t.
[0036] When step 520 is selected, a machine learning process can be utilized
to predict the fluid
pressure vs. fluid volume data or to predict the fitted coefficients. For
example, one such process
can be to collect production data for all adjacent borehole systems that have
fluid injection data.
This can be represented as a time history of the production volume for gas
(Qg), oil (Q,), and
water (Q14,). The production volume can be converted to bottom hole production
conditions
utilizing a formation factor as shown in Equation 2.
Equation 2: Example bottom hole production conversion
Qp = Qofo + Qgfg + Qw
where Qp is the computed production volume that can be utilized as the input
parameters in the
subsequent method steps,
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Date Recue/Date Received 2020-12-23
fi is the formation oil factor, and
fg is the formation gas factor.
[0037] The production flow rate can be computed utilizing Equation 3. A
general fit can be
computed where time (x-axis) and inverse flow rate (y-axis) can be utilized to
determine the
slope (m) and intercept (c). For example, Equation 4 demonstrates a linear fit
and the x-axis is a
square root of time.
Equation 3: Example production flow rate
qp = dQpIdt
Equation 4: Example linear fit
1/qp = m Vt + c
[0038] A machine learning model can utilize the computed Qp, m, and c factors
along with
corresponding injection data. In some aspects, additional factors can be
included in the machine
learning model. For one or more of the adjacent borehole systems that do not
have
corresponding input parameters, the machine learning model can be used to
estimate the input
parameters for those respective adjacent borehole systems.
[0039] From step 510 or step 520, method 500 proceeds to a step 530, where the
active borehole
treatment stage can be in progress, such as pumping a fluid into the active
borehole. The
treatment stage follows the treatment plan and can have various combinations
of flow rate,
pressure, and composition changes over the time interval of the treatment
stage. Proceeding to a
step 540, the processes can monitor the input parameters from one or more
adjacent borehole
systems as the treatment stage is in progress. The monitoring can receive or
determine a fracture
hit threshold that can be utilized to determine when a pressure change in an
adjacent borehole
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Date Recue/Date Received 2020-12-23
system is sufficient to trigger further analysis for a potential leak-off
event. The further analysis
can include calculating volume changes compared to the expected volume change,
for example,
using Equation 1.
[0040] FIG. 3 can be used to demonstrate an example analysis. Pressure point
P1 330 (Pi)
corresponds to the fluid pressure at the fracture hit event and pressure point
P2 335 (P2) is a fluid
pressure at a later time during the treatment stage. The fluid volume leaking
off to the adjacent
borehole system, e.g., a void, a depleted reservoir, or an adjacent borehole,
can be determined
using the function shown in Equation 5. If a look-up table approach can be
utilized, then
Equation 6 can be used to calculate the adjacent borehole volume. If the
coefficients of the fluid
pressure vs. fluid volume curve are utilized as shown in Equation 1, then for
this example,
Equation 7 can be utilized. The volume of pumped fluid lost to the void
represents the severity
of the interference. In some aspects, a control action such as adjusting the
pumping rate,
adjusting the composition, or dropping diverters can be deployed if this value
does not satisfy a
fracture hit threshold.
Equation 5: Example adjacent borehole volume function
AV = f (Pi, t1,P2, t2)
Equation 6: Example adjacent borehole volume using a look table
AV = V(P2) ¨ V(Pi)
Equation 7: Example adjacent borehole volume using Equation 1 coefficients
AV = Cp(P2 ¨ P1) ¨ 2 Lk(Vt2 + to ¨ Vti + to)
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[0041] The fracture hit event detected at Pi can be determined by an
algorithm. For example,
graph 400 in FIG. 4 can be utilized to demonstrate one potential algorithm.
Input parameters
from adjacent boreholes can be received over an initial time interval, for
example, ten minutes or
other time intervals. In some aspects, the time interval can start at the
start of the active borehole
treatment stage. In some aspects, the time interval can start prior to or
after the start of the
treatment stage.
[0042] The input parameters can be used in correspondence to the pumped fluid
pressure and
pumped fluid flow rate, such as shown in FIG. 3 and FIG. 4. A curve fit, e.g.,
general fit,
operation can be applied starting at the to time period. This is represented
by fitted line 432 in
FIG. 4 and is shown by example using a linear fit in Equation 8, such that the
error represented
by Equation 9 is minimized.
Equation 8: Example linear line fit
p = bt + c
Equation 9: Example error minimization
IWO P(ti))2
where 15(0 is the linear fit to the data received at p(ti);
b is the slope; and
c is the intercept.
[0043] In some aspects, the fracture hit threshold can be determined by an
input parameter, for
example, provided by a user or a computing system, such as a well site
controller. In some
aspects, the fracture hit threshold can be determined using a confidence
interval on the fit, for
example, a standard deviation as shown in Equation 10.
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Date Recue/Date Received 2020-12-23
Equation 10: Example standard deviation for determining a confidence interval
P(ti))2
=
N ¨ 1
where N is the number of samples in the learn 440 portion. In some aspects,
the fracture hit
threshold can be defined as p + co- where c represents a multiplier. In some
aspects, the
multiplier can be 2.5 to 3.0, and in other aspects, other values can be used.
Threshold lines 434
represent the determined fracture hit threshold as applied to the received
input parameters.
[0044] The curve fit and the fracture hit threshold can be extended into the
predict 445 portion
by setting the time variable t in the regression fit. If the regression fit in
the predict 445 portion
satisfies the fracture hit threshold then that time interval can be moved into
the learn 440 portion
and a new predict 445 portion can be estimated by increasing the time variable
t. The analysis
can be performed again using the new time interval and the received input
parameters
corresponding to the new time interval.
[0045] If the regression fit in the predict 445 portion does not satisfy the
fracture hit threshold
then a potential leak-off event can be detected at the time where the
regression fit fails, for
example, point 430. To determine whether the potential leak-off event is a
true leak-off event,
additional analysis can be applied.
[0046] In some aspects, a leak-off linear regression can be fit to the data in
the predict 445
portion. If the slope suggests an overall increase of pressure, then the
potential event can be
assumed as a leak-off event. In some aspects, the potential event detection
can utilize an
estimation of pumped fluid entering the adjacent borehole. If the amount of
pumped fluid
entering the adjacent borehole after the time of the potential event exceeds a
leak-off threshold,
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Date Recue/Date Received 2020-12-23
then the potential event can be assumed a leak-off event. The leak-off
threshold can be part of
the input parameters received or can be defaulted to a pre-determine
parameter.
[0047] Once the leak-off event is detected, an appropriate control technique
can be performed to
mitigate the leak-off event. The pressure reading past the leak-off event
detection point, for
example point 430, in correspondence to the volume of the pumped fluid
estimated to have
flowed into the adjacent borehole, can be utilized to assess the effect of the
control strategy.
[0048] Proceeding to a step 570, the treatment stage efficiency can be
analyzed and adjustments
can be determined. In some aspects, the adjustments can be a change to the
pumped fluid
pressure, pumped fluid flow rate, or pumped fluid volume. In some aspects, the
adjustments can
be a change in the pumped fluid composition, an addition or subtraction of
added material such
as diverter material, or other compositional changes. As the adjustments are
implemented in the
treatment stage, the processes as described herein can be performed in real-
time, near real-time,
or at proscribed time intervals to update the leak-off event data. Further
adjustments can be
made as needed. The adjustments can be implemented by a borehole device, such
as a well site
controller, or by a user. Method 500 ends at a step 590
[0049] FIG. 6 is an illustration of a block diagram of an example leak-off
estimator system 600,
which can be implemented using a pumping system and one or more computing
systems, for
example, a well site controller, a reservoir controller, a data center, a
cloud environment, a
server, a laptop, a smartphone, a mobile phone, a tablet, and other computing
systems. The
computing system can be located proximate the well site, or a distance from
the well site, such as
in a data center, cloud environment, or corporate location. The computing
system can be a
distributed system having a portion located proximate the well site and a
portion located
remotely from the well site.
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Date Recue/Date Received 2020-12-23
[0050] Leak-off estimator system 600, or a portion thereof, can be implemented
as an
application, a code library, a dynamic link library, a function, a module,
other software
implementation, or combinations thereof. In some aspects, leak-off estimator
system 600 can be
implemented in hardware, such as a ROM, a graphics processing unit, or other
hardware
implementation. In some aspects, leak-off estimator system 600 can be
implemented partially as
a software application and partially as a hardware implementation.
[0051] Leak-off estimator system 600 includes an active borehole system 610
with downhole
sensors 620, such as fluid pressure and temperature sensors, an adjacent
borehole system 612
with downhole sensors 622, such as fluid pressure and temperature sensors.
There can be
additional adjacent borehole systems. Active borehole system 610 also includes
a pumping
system capable of pumping a fluid with or without additional material, such as
chemicals,
additives, diverter material, and other downhole material, downhole into the
borehole.
Communicatively coupled to active borehole system 610 and, optionally,
adjacent borehole
system 612, is one or more well site controllers 630. In some aspects, a
pumping plan generator
632 is communicatively coupled to well site controllers 630. In some aspects,
pumping plan
generator 632 is part of well site controllers 630. A user system 634 is
communicatively coupled
to well site controllers 630 and pumping plan generator 632 to allow users to
enter the input
parameters, view analysis, and be able to direct adjustments to a treatment
stage of active
borehole system 610.
[0052] A leak-off event estimator 650 is communicatively coupled to well site
controllers 630,
pumping plan generator 632, and user system 634. Leak-off event estimator 650
is capable of
receiving input parameters from one or more sources, for example, from a
machine learning
model, from downhole sensors 622, from well site controllers 630, from user
system 634, or
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from other systems associated with the active borehole system 610. Leak-off
event estimator
650 can perform the analysis, processes, and methods as described herein to
determine a leak-off
event, and to provide the leak-off event data to pumping plan generator 632,
well site controllers
630, or user system 634.
[0053] The leak-off event data can be utilized by a user to adjust a treatment
plan, or by pumping
plan generator 632 to adjust a treatment plan which can be implemented by
other systems. The
receipt of input parameters and the subsequent analysis and processes can be
performed in real-
time, near-real-time, or at a periodic time interval to allow updated leak-off
event data to be
analyzed as a treatment stage is in progress at active borehole system 610.
[0054] In some aspects, leak-off event estimator 650 can be part of well site
controllers 630. In
some aspects, leak-off event estimator 650 can be part of pumping plan
generator 632. In some
aspects, leak-off event estimator 650 can communicate with other systems, for
example, a data
center, cloud environment, or other computing systems to provide the leak-off
event data. In
some aspects, leak-off event estimator 650 can generate visual graphs. In some
aspects, leak-off
event estimator 650 can provide the leak-off event data to another system for
decision making
and processing.
[0055] A memory or data storage of leak-off event estimator 650 can be
configured to store the
processes and algorithms for directing the operation of leak-off event
estimator 650. Leak-off
event estimator 650 can include a processor that is configured to operate
according to the
analysis operations and algorithms disclosed herein, and an interface to
communicate (transmit
and receive) data.
[0056] A portion of the above-described apparatus, systems or methods may be
embodied in or
performed by various analog or digital data processors, wherein the processors
are programmed
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Date Recue/Date Received 2020-12-23
or store executable programs of sequences of software instructions to perform
one or more of the
steps of the methods. A processor may be, for example, a programmable logic
device such as a
programmable array logic (PAL), a generic array logic (GAL), a field
programmable gate arrays
(FPGA), or another type of computer processing device (CPD). The software
instructions of
such programs may represent algorithms and be encoded in machine-executable
form on non-
transitory digital data storage media, e.g., magnetic or optical disks, random-
access memory
(RAM), magnetic hard disks, flash memories, and/or read-only memory (ROM), to
enable
various types of digital data processors or computers to perform one, multiple
or all of the steps
of one or more of the above-described methods, or functions, systems or
apparatuses described
herein.
[0057] Portions of disclosed examples or embodiments may relate to computer
storage products
with a non-transitory computer-readable medium that have program code thereon
for performing
various computer-implemented operations that embody a part of an apparatus,
device or carry
out the steps of a method set forth herein. Non-transitory used herein refers
to all computer-
readable media except for transitory, propagating signals. Examples of non-
transitory computer-
readable media include, but are not limited to: magnetic media such as hard
disks, floppy disks,
and magnetic tape; optical media such as CD-ROM disks; magneto-optical media
such as floppy
disks; and hardware devices that are specially configured to store and execute
program code,
such as ROM and RAM devices. Examples of program code include both machine
code, such as
produced by a compiler, and files containing higher level code that may be
executed by the
computer using an interpreter.
[0058] In interpreting the disclosure, all terms should be interpreted in the
broadest possible
manner consistent with the context. In particular, the terms "comprises" and
"comprising" should
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Date Recue/Date Received 2020-12-23
be interpreted as referring to elements, components, or steps in a non-
exclusive manner,
indicating that the referenced elements, components, or steps may be present,
or utilized, or
combined with other elements, components, or steps that are not expressly
referenced.
[0059] Those skilled in the art to which this application relates will
appreciate that other and
further additions, deletions, substitutions and modifications may be made to
the described
embodiments. It is also to be understood that the terminology used herein is
for the purpose of
describing particular embodiments only, and is not intended to be limiting,
because the scope of
the present disclosure will be limited only by the claims. Unless defined
otherwise, all technical
and scientific terms used herein have the same meaning as commonly understood
by one of
ordinary skill in the art to which this disclosure belongs. Although any
methods and materials
similar or equivalent to those described herein can also be used in the
practice or testing of the
present disclosure, a limited number of the exemplary methods and materials
are described
herein.
[0060] Each of the aspects as disclosed in the SUMMARY section can have one or
more of the
following additional elements in combination. Element 1: adjusting the
treatment stage by
adjusting one or more of a pumped fluid volume, a pumped fluid flow rate, a
pumped fluid
pressure, or a pumped fluid composition. Element 2: wherein the pumped fluid
composition can
be adjusted by one or more of increasing or decreasing one or more of an oil,
a water, a brine, a
slurry, a proppant, a chemical, an additive, or a diverter material. Element
3: wherein the input
parameters are received at the periodic time interval from one or more sensors
in the one or more
adjacent boreholes, wherein the input parameters can include the adjacent
fluid volume and the
adjacent fluid pressure relationship over a recording time interval. Element
4: wherein the input
parameters are utilized as a look up table to obtain the adjacent fluid volume
from the adjacent
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Date Recue/Date Received 2020-12-23
fluid pressure. Element 5: wherein the adjacent fluid volume at a specified
time and specified
fluid pressure is computed utilizing a system compressibility parameter, a
leak-off coefficient,
and a time shift factor. Element 6: wherein the adjacent fluid volume at a
specified time and
specified fluid pressure is computed utilizing a machine learning model
trained using an estimate
of a production volume of an oil, a gas, and a water for the one or more
adjacent boreholes.
Element 7: wherein the fracture hit threshold is determined from a standard
deviation and a
multiplier. Element 8: a pumping plan generator, capable of adjusting the at
least one treatment
stage and communicating with the well site controller. Element 9: a machine
learning model,
capable of estimating a fluid volume utilizing a production volume of oil, a
production volume of
water, and a production volume of gas from the at least one adjacent borehole.
Element 10: a
sensor, capable of communicating a measured fluid pressure as an input
parameter to the leak-off
event estimator, wherein the sensor measures fluid pressure in the at least
one adjacent borehole.
Element 11: wherein the treatment stage is adjusted utilizing an output of the
leak-off event
estimator, where the treatment stage adjusts a pumped fluid volume, a pumped
fluid flow rate, a
pumped fluid pressure, or a pumped fluid composition. Element 12: wherein the
periodic time
interval is real-time or near real-time. Element 13: adjusting the treatment
stage by directing one
or more of a pumped fluid volume, a pumped fluid flow rate, a pumped fluid
pressure, or a
pumped fluid composition.
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